Simulating the Effects of Common and Specific Abilities on Test Performance: An Evaluation of Factor Analysis Purpose Factor analysis is a useful technique to aid in organizing multivariate data characterizing speech, language, and auditory abilities. However, knowledge of the limitations of factor analysis is essential for proper interpretation of results. The present study used simulated test scores to illustrate some characteristics of factor analysis. Method ... Research Article
Research Article  |   October 01, 2014
Simulating the Effects of Common and Specific Abilities on Test Performance: An Evaluation of Factor Analysis
 
Author Affiliations & Notes
  • Dennis J. McFarland
    Wadsworth Center, New York State Department of Health, Albany
  • Disclosure: The author has declared that no competing interests existed at the time of publication.
    Disclosure: The author has declared that no competing interests existed at the time of publication.×
  • Correspondence to Dennis J. McFarland: mcfarlan@wadsworth.org
  • Editor: Craig Champlin
    Editor: Craig Champlin×
  • Associate Editor: Jeffrey Weihing
    Associate Editor: Jeffrey Weihing×
Article Information
Research Issues, Methods & Evidence-Based Practice / Hearing / Research Articles
Research Article   |   October 01, 2014
Simulating the Effects of Common and Specific Abilities on Test Performance: An Evaluation of Factor Analysis
Journal of Speech, Language, and Hearing Research, October 2014, Vol. 57, 1919-1928. doi:10.1044/2014_JSLHR-H-13-0166
History: Received June 28, 2013 , Revised November 1, 2013 , Accepted March 1, 2014
 
Journal of Speech, Language, and Hearing Research, October 2014, Vol. 57, 1919-1928. doi:10.1044/2014_JSLHR-H-13-0166
History: Received June 28, 2013; Revised November 1, 2013; Accepted March 1, 2014

Purpose Factor analysis is a useful technique to aid in organizing multivariate data characterizing speech, language, and auditory abilities. However, knowledge of the limitations of factor analysis is essential for proper interpretation of results. The present study used simulated test scores to illustrate some characteristics of factor analysis.

Method Linear models were used to simulate test scores that were determined by multiple latent variables. These simulated test scores were evaluated with principal components analysis and, in certain cases, structural equation modeling. In addition, a subset of simulated individuals characterized by poor test performance was examined.

Results The number of factors recovered and their identity do not necessarily correspond to the structure of the latent variables that generated the test scores. The first principal component may represent variance from multiple uncorrelated sources. Practices such as correction or control for general cognitive ability may produce misleading results.

Conclusions Inferences from the results of factor analysis should be primarily about the structure of test batteries rather than the structure of human mental abilities. Researchers and clinicians should consider multiple sources of evidence to evaluate hypotheses about the processes generating test results.

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